Comparison of Two Neural Network Approaches for Identification of Nonlinear Systems

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概要

• 論文の詳細を見る

• Although the subject of system identification is well developed for linear systems, the same is not true for the nonlinear case. Since multilayer neural networks (MNNs) can be seen as very versatile feedforward blocks with great mapping capability and learning ability, their use for system identification has been the subject of several recent studies. This paper presents two neuro-identifiers for general systems and compares their main characteristics. Numerical comparison based on simulation will be presented at the conference.

• 一般社団法人情報処理学会の論文
• 1993-09-27

著者

• Tanomaru Julio

  Faculty Of Engineering The University Of Tokushima

• Tanomaru Julio

  Faculty Of Engineering University Of Tokushima

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• Comparison of Two Neural Network Approaches for Identification of Nonlinear Systems

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